



import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


a      :  Any			     =			logging.get_logger(__name__)

a      :  Dict			     =			{
    'vocab_file': 'vocab.txt',
    'merges_file': 'bpe.codes',
}

a      :  Union[str, Any]			     =			{
    'vocab_file': {
        'vinai/phobert-base': 'https://huggingface.co/vinai/phobert-base/resolve/main/vocab.txt',
        'vinai/phobert-large': 'https://huggingface.co/vinai/phobert-large/resolve/main/vocab.txt',
    },
    'merges_file': {
        'vinai/phobert-base': 'https://huggingface.co/vinai/phobert-base/resolve/main/bpe.codes',
        'vinai/phobert-large': 'https://huggingface.co/vinai/phobert-large/resolve/main/bpe.codes',
    },
}

a      :  List[str]			     =			{
    'vinai/phobert-base': 256,
    'vinai/phobert-large': 256,
}







def  lowerCAmelCase_	(lowerCAmelCase__:		int  ):





			"""simple docstring"""


			UpperCAmelCase_:		Optional[int]							      =     set()
			UpperCAmelCase_:		Optional[Any]							      =     word[0]
			for char in word[1:]:
						pairs.add((prev_char, char)  )
						UpperCAmelCase_:		Tuple							      =     char

			UpperCAmelCase_:		Optional[int]							      =     set(lowerCAmelCase__  )
			return pairs







class 				_a				(   _lowerCAmelCase					):
			A      		=	VOCAB_FILES_NAMES
			A      		=	PRETRAINED_VOCAB_FILES_MAP
			A      		=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES

			def __init__(self,   SCREAMING_SNAKE_CASE_,   SCREAMING_SNAKE_CASE_,   SCREAMING_SNAKE_CASE_="<s>",   SCREAMING_SNAKE_CASE_="</s>",   SCREAMING_SNAKE_CASE_="</s>",   SCREAMING_SNAKE_CASE_="<s>",   SCREAMING_SNAKE_CASE_="<unk>",   SCREAMING_SNAKE_CASE_="<pad>",   SCREAMING_SNAKE_CASE_="<mask>",   **SCREAMING_SNAKE_CASE_,   )       ->   Dict:
						super().__init__(
						    bos_token=SCREAMING_SNAKE_CASE_,   eos_token=SCREAMING_SNAKE_CASE_,   unk_token=SCREAMING_SNAKE_CASE_,   sep_token=SCREAMING_SNAKE_CASE_,   cls_token=SCREAMING_SNAKE_CASE_,   pad_token=SCREAMING_SNAKE_CASE_,   mask_token=SCREAMING_SNAKE_CASE_,   **SCREAMING_SNAKE_CASE_,   )

						UpperCAmelCase_:		List[str]							      =     vocab_file
						UpperCAmelCase_:		Dict							      =     merges_file

						UpperCAmelCase_:		List[str]							      =     {}
						UpperCAmelCase_:		Any							      =     0
						UpperCAmelCase_:		Dict							      =     1
						UpperCAmelCase_:		Union[str, Any]							      =     2
						UpperCAmelCase_:		List[Any]							      =     3

						self.add_from_file(SCREAMING_SNAKE_CASE_					)

						UpperCAmelCase_:		Tuple							      =     {v: k for k, v in self.encoder.items()}

						with open(SCREAMING_SNAKE_CASE_,   encoding="""utf-8"""					) as merges_handle:
									UpperCAmelCase_:		Tuple							      =     merges_handle.read().split("""\n"""					)[:-1]
						UpperCAmelCase_:		Union[str, Any]							      =     [tuple(merge.split()[:-1]					) for merge in merges]
						UpperCAmelCase_:		str							      =     dict(zip(SCREAMING_SNAKE_CASE_,   range(len(SCREAMING_SNAKE_CASE_					)					)					)					)
						UpperCAmelCase_:		int							      =     {}

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_,   SCREAMING_SNAKE_CASE_ = None					)       ->   List[int]:

						if token_ids_a is None:
									return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
						UpperCAmelCase_:		List[str]							      =     [self.cls_token_id]
						UpperCAmelCase_:		int							      =     [self.sep_token_id]
						return cls + token_ids_a + sep + sep + token_ids_a + sep

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_,   SCREAMING_SNAKE_CASE_ = None,   SCREAMING_SNAKE_CASE_ = False					)       ->   List[int]:

						if already_has_special_tokens:
									return super().get_special_tokens_mask(
									    token_ids_a=SCREAMING_SNAKE_CASE_,   token_ids_a=SCREAMING_SNAKE_CASE_,   already_has_special_tokens=SCREAMING_SNAKE_CASE_					)

						if token_ids_a is None:
									return [1] + ([0] * len(SCREAMING_SNAKE_CASE_					)) + [1]
						return [1] + ([0] * len(SCREAMING_SNAKE_CASE_					)) + [1, 1] + ([0] * len(SCREAMING_SNAKE_CASE_					)) + [1]

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_,   SCREAMING_SNAKE_CASE_ = None					)       ->   List[int]:
						UpperCAmelCase_:		Dict							      =     [self.sep_token_id]
						UpperCAmelCase_:		Tuple							      =     [self.cls_token_id]

						if token_ids_a is None:
									return len(cls + token_ids_a + sep					) * [0]
						return len(cls + token_ids_a + sep + sep + token_ids_a + sep					) * [0]

			@property
			def      __snake_case       (self					)       ->   List[str]:
						return len(self.encoder					)

			def      __snake_case       (self					)       ->   int:
						return dict(self.encoder,   **self.added_tokens_encoder					)

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_					)       ->   Optional[int]:
						if token in self.cache:
									return self.cache[token]
						UpperCAmelCase_:		Optional[int]							      =     tuple(SCREAMING_SNAKE_CASE_					)
						UpperCAmelCase_:		Any							      =     tuple(list(word[:-1]					) + [word[-1] + """</w>"""]					)
						UpperCAmelCase_:		int							      =     get_pairs(SCREAMING_SNAKE_CASE_					)

						if not pairs:
									return token

						while True:
									UpperCAmelCase_:		int							      =     min(SCREAMING_SNAKE_CASE_,   key=lambda SCREAMING_SNAKE_CASE_					: self.bpe_ranks.get(SCREAMING_SNAKE_CASE_,   float("""inf"""					)					)					)
									if bigram not in self.bpe_ranks:
												break
									UpperCAmelCase_      ,							UpperCAmelCase_:		List[Any]							      =     bigram
									UpperCAmelCase_:		Any							      =     []
									UpperCAmelCase_:		List[str]							      =     0
									while i < len(SCREAMING_SNAKE_CASE_					):
												try:
															UpperCAmelCase_:		Any							      =     word.index(SCREAMING_SNAKE_CASE_,   SCREAMING_SNAKE_CASE_					)
												except ValueError:
															new_word.extend(word[i:]					)
															break
												else:
															new_word.extend(word[i:j]					)
															UpperCAmelCase_:		Optional[Any]							      =     j

												if word[i] == first and i < len(SCREAMING_SNAKE_CASE_					) - 1 and word[i + 1] == second:
															new_word.append(first + second					)
															i += 2
												else:
															new_word.append(word[i]					)
															i += 1
									UpperCAmelCase_:		Dict							      =     tuple(SCREAMING_SNAKE_CASE_					)
									UpperCAmelCase_:		List[Any]							      =     new_word
									if len(SCREAMING_SNAKE_CASE_					) == 1:
												break
									else:
												UpperCAmelCase_:		List[str]							      =     get_pairs(SCREAMING_SNAKE_CASE_					)
						UpperCAmelCase_:		str							      =     """@@ """.join(SCREAMING_SNAKE_CASE_					)
						UpperCAmelCase_:		str							      =     word[:-4]
						UpperCAmelCase_:		List[str]							      =     word
						return word

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_					)       ->   Union[str, Any]:
						UpperCAmelCase_:		str							      =     []

						UpperCAmelCase_:		Any							      =     re.findall(R"""\S+\n?""",   SCREAMING_SNAKE_CASE_					)

						for token in words:
									split_tokens.extend(list(self.bpe(SCREAMING_SNAKE_CASE_					).split(""" """					)					)					)
						return split_tokens

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_					)       ->   int:
						return self.encoder.get(SCREAMING_SNAKE_CASE_,   self.encoder.get(self.unk_token					)					)

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_					)       ->   Any:
						return self.decoder.get(SCREAMING_SNAKE_CASE_,   self.unk_token					)

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_					)       ->   List[str]:
						UpperCAmelCase_:		Tuple							      =     """ """.join(SCREAMING_SNAKE_CASE_					).replace("""@@ """,   """"""					).strip()
						return out_string

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_,   SCREAMING_SNAKE_CASE_ = None					)       ->   Tuple[str]:
						if not os.path.isdir(SCREAMING_SNAKE_CASE_					):
									logger.error(f'Vocabulary path ({save_directory}) should be a directory'					)
									return
						UpperCAmelCase_:		Dict							      =     os.path.join(
						    SCREAMING_SNAKE_CASE_,   (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]					)
						UpperCAmelCase_:		Optional[int]							      =     os.path.join(
						    SCREAMING_SNAKE_CASE_,   (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""]					)

						if os.path.abspath(self.vocab_file					) != os.path.abspath(SCREAMING_SNAKE_CASE_					):
									copyfile(self.vocab_file,   SCREAMING_SNAKE_CASE_					)

						if os.path.abspath(self.merges_file					) != os.path.abspath(SCREAMING_SNAKE_CASE_					):
									copyfile(self.merges_file,   SCREAMING_SNAKE_CASE_					)

						return out_vocab_file, out_merge_file

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_					)       ->   Optional[Any]:
						if isinstance(SCREAMING_SNAKE_CASE_,   SCREAMING_SNAKE_CASE_					):
									try:
												with open(SCREAMING_SNAKE_CASE_,   """r""",   encoding="""utf-8"""					) as fd:
															self.add_from_file(SCREAMING_SNAKE_CASE_					)
									except FileNotFoundError as fnfe:
												raise fnfe
									except UnicodeError:
												raise Exception(f'Incorrect encoding detected in {f}, please rebuild the dataset'					)
									return

						UpperCAmelCase_:		Optional[Any]							      =     f.readlines()
						for lineTmp in lines:
									UpperCAmelCase_:		Union[str, Any]							      =     lineTmp.strip()
									UpperCAmelCase_:		Union[str, Any]							      =     line.rfind(""" """					)
									if idx == -1:
												raise ValueError("""Incorrect dictionary format, expected '<token> <cnt>'"""					)
									UpperCAmelCase_:		Optional[int]							      =     line[:idx]
									UpperCAmelCase_:		Any							      =     len(self.encoder					)











import logging
from dataclasses import dataclass, field
from typing import Optional

from seqaseq_trainer import arg_to_scheduler

from transformers import TrainingArguments


a      :  Optional[int]			     =			logging.getLogger(__name__)







@dataclass
class 				_a				(   _lowerCAmelCase					):
			A      		=	field(
			    default=0.0 ,		metadata={'''help''': '''The label smoothing epsilon to apply (if not zero).'''}					)
			A      		=	field(default=_lowerCAmelCase ,		metadata={'''help''': '''Whether to SortishSamler or not.'''}					)
			A      		=	field(
			    default=_lowerCAmelCase ,		metadata={'''help''': '''Whether to use generate to calculate generative metrics (ROUGE, BLEU).'''}					)
			A      		=	field(default=_lowerCAmelCase ,		metadata={'''help''': '''whether to use adafactor'''}					)
			A      		=	field(
			    default=_lowerCAmelCase ,		metadata={'''help''': '''Encoder layer dropout probability. Goes into model.config.'''}					)
			A      		=	field(
			    default=_lowerCAmelCase ,		metadata={'''help''': '''Decoder layer dropout probability. Goes into model.config.'''}					)
			A      		=	field(default=_lowerCAmelCase ,		metadata={'''help''': '''Dropout probability. Goes into model.config.'''}					)
			A      		=	field(
			    default=_lowerCAmelCase ,		metadata={'''help''': '''Attention dropout probability. Goes into model.config.'''}					)
			A      		=	field(
			    default='''linear''' ,		metadata={'''help''': F'''Which lr scheduler to use. Selected in {sorted(arg_to_scheduler.keys()					)}'''} ,		)






